A new technical paper titled \u201cSolving the compute crisis with physics-based ASICs\u201d was published by researchers at Normal Computing Corporation, ARIA, UC Santa Barbara, University of Pennsylvania, Santa Fe Institute, Cornell University. Advanced Research Projects Agency \u2013 Energy and Yale University.<\/p>\n
Abstract
\u201cEscalating artificial intelligence (AI) demands expose a critical \u201ccompute crisis\u201d characterized by unsustainable energy consumption, prohibitive training costs, and the approaching limits of conventional CMOS scaling. Physics-based Application-Specific Integrated Circuits (ASICs) present a transformative paradigm by directly harnessing intrinsic physical dynamics for computation rather than expending resources to enforce idealized digital abstractions. By relaxing the constraints needed for traditional ASICs, like enforced statelessness, unidirectionality, determinism, and synchronization, these devices aim to operate as exact realizations of physical processes, offering substantial gains in energy efficiency and computational throughput. This approach enables novel co-design strategies, aligning algorithmic requirements with the inherent computational primitives of physical systems. Physics-based ASICs could accelerate critical AI applications like diffusion models, sampling, optimization, and neural network inference as well as traditional computational workloads like scientific simulation of materials and molecules. Ultimately, this vision points towards a future of heterogeneous, highly-specialized computing platforms capable of overcoming current scaling bottlenecks and unlocking new frontiers in computational power and efficiency.\u201d<\/p>\n